Search ga_ls8c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2022-10-27 10:20:43	ga_ls8c_ard_3-2-1_100079_2022-10-27_final
2022-10-31 11:34:54	ga_ls8c_ard_3-2-1_112079_2022-10-31_final
2022-10-31 11:35:18	ga_ls8c_ard_3-2-1_112080_2022-10-31_final
2022-11-01 10:35:18	ga_ls8c_ard_3-2-1_103069_2022-11-01_final
2022-11-04 09:34:06	ga_ls8c_ard_3-2-1_092086_2022-11-04_final
2022-11-04 11:09:47	ga_ls8c_ard_3-2-1_108078_2022-11-04_final
2022-11-05 10:16:33	ga_ls8c_ard_3-2-1_099084_2022-11-05_final
2022-11-06 10:53:49	ga_ls8c_ard_3-2-1_106069_2022-11-06_final
2022-11-06 10:54:37	ga_ls8c_ard_3-2-1_106071_2022-11-06_final
2022-11-06 10:57:01	ga_ls8c_ard_3-2-1_106077_2022-11-06_final
2022-11-06 10:59:01	ga_ls8c_ard_3-2-1_106082_2022-11-06_final
2022-11-08 10:41:03	ga_ls8c_ard_3-2-1_104068_2022-11-08_final
2022-11-09 09:49:49	ga_ls8c_ard_3-2-1_095079_2022-11-09_final
2022-11-09 09:52:36	ga_ls8c_ard_3-2-1_095086_2022-11-09_final
2022-11-18 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-11-18_final
2022-11-18 09:44:19	ga_ls8c_ard_3-2-1_094081_2022-11-18_final
2022-11-20 11:10:28	ga_ls8c_ard_3-2-1_108080_2022-11-20_final
2022-11-22 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-11-21_final
2022-11-23 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-11-23_final
2022-11-23 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-11-23_final
2022-11-25 09:51:21	ga_ls8c_ard_3-2-1_095083_2022-11-25_final
2022-11-25 09:52:09	ga_ls8c_ard_3-2-1_095085_2022-11-25_final
2022-11-25 11:28:38	ga_ls8c_ard_3-2-1_111079_2022-11-25_final
2022-11-29 11:04:43	ga_ls8c_ard_3-2-1_107081_2022-11-29_final
2022-11-30 10:10:42	ga_ls8c_ard_3-2-1_098085_2022-11-30_final
2022-12-01 10:50:22	ga_ls8c_ard_3-2-1_105076_2022-12-01_final
2022-12-02 09:53:33	ga_ls8c_ard_3-2-1_096073_2022-12-02_final
2022-12-02 09:54:21	ga_ls8c_ard_3-2-1_096075_2022-12-02_final
2022-12-02 11:34:02	ga_ls8c_ard_3-2-1_112077_2022-12-02_final
2022-12-04 09:44:22	ga_ls8c_ard_3-2-1_094081_2022-12-04_final
2022-12-06 09:30:25	ga_ls8c_ard_3-2-1_092077_2022-12-06_final
2022-12-06 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-12-06_final
2022-12-07 10:15:40	ga_ls8c_ard_3-2-1_099082_2022-12-07_final
2022-12-07 10:16:28	ga_ls8c_ard_3-2-1_099084_2022-12-07_final
2022-12-08 10:53:20	ga_ls8c_ard_3-2-1_106068_2022-12-08_final
2022-12-14 10:20:36	ga_ls8c_ard_3-2-1_100079_2022-12-14_final
2022-12-15 09:22:34	ga_ls8c_ard_3-2-1_091073_2022-12-14_final
2022-12-19 10:35:05	ga_ls8c_ard_3-2-1_103069_2022-12-19_final
2022-12-20 09:43:02	ga_ls8c_ard_3-2-1_094078_2022-12-20_final
2022-12-22 11:10:19	ga_ls8c_ard_3-2-1_108080_2022-12-22_final
2022-12-26 10:42:25	ga_ls8c_ard_3-2-1_104072_2022-12-26_final
2022-12-28 10:33:16	ga_ls8c_ard_3-2-1_102080_2022-12-28_final
2022-12-29 11:15:20	ga_ls8c_ard_3-2-1_109077_2022-12-29_final
2022-12-30 10:18:55	ga_ls8c_ard_3-2-1_100075_2022-12-30_final
2022-12-31 11:04:34	ga_ls8c_ard_3-2-1_107081_2022-12-31_final
2023-01-01 10:06:33	ga_ls8c_ard_3-2-1_098075_2023-01-01_final
2023-01-03 09:55:00	ga_ls8c_ard_3-2-1_096077_2023-01-03_final
2023-01-05 09:45:02	ga_ls8c_ard_3-2-1_094083_2023-01-05_final
2023-01-06 10:25:05	ga_ls8c_ard_3-2-1_101075_2023-01-06_final
2023-01-11 10:41:36	ga_ls8c_ard_3-2-1_104070_2023-01-11_final
2023-01-12 09:49:33	ga_ls8c_ard_3-2-1_095079_2023-01-12_final
2023-01-12 09:51:09	ga_ls8c_ard_3-2-1_095083_2023-01-12_final
2023-01-12 09:52:45	ga_ls8c_ard_3-2-1_095087_2023-01-12_final
2023-01-16 09:26:22	ga_ls8c_ard_3-2-1_091083_2023-01-15_final
2023-01-16 11:04:27	ga_ls8c_ard_3-2-1_107081_2023-01-16_final
2023-01-17 11:47:18	ga_ls8c_ard_3-2-1_114080_2023-01-17_final
2023-01-21 09:42:56	ga_ls8c_ard_3-2-1_094078_2023-01-21_final
2023-01-21 11:22:13	ga_ls8c_ard_3-2-1_110079_2023-01-21_final
2023-01-23 11:11:05	ga_ls8c_ard_3-2-1_108082_2023-01-23_final
2023-01-25 10:55:09	ga_ls8c_ard_3-2-1_106073_2023-01-25_final
2023-01-29 10:29:15	ga_ls8c_ard_3-2-1_102070_2023-01-29_final
2023-01-30 09:36:01	ga_ls8c_ard_3-2-1_093076_2023-01-30_final
2023-02-01 09:27:39	ga_ls8c_ard_3-2-1_091086_2023-01-31_final
2023-02-06 09:45:47	ga_ls8c_ard_3-2-1_094085_2023-02-06_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-09 10:15:28	ga_ls8c_ard_3-2-1_099082_2023-02-09_final
2023-02-10 09:19:02	ga_ls8c_ard_3-2-1_090080_2023-02-09_final
2023-02-10 10:56:43	ga_ls8c_ard_3-2-1_106077_2023-02-10_final
2023-02-14 10:31:08	ga_ls8c_ard_3-2-1_102075_2023-02-14_final
2023-02-15 11:15:59	ga_ls8c_ard_3-2-1_109079_2023-02-15_final
2023-02-15 11:16:23	ga_ls8c_ard_3-2-1_109080_2023-02-15_final
2023-02-17 09:23:31	ga_ls8c_ard_3-2-1_091076_2023-02-16_final
2023-02-17 09:24:19	ga_ls8c_ard_3-2-1_091078_2023-02-16_final
2023-02-17 11:04:23	ga_ls8c_ard_3-2-1_107081_2023-02-17_final
2023-02-18 11:47:14	ga_ls8c_ard_3-2-1_114080_2023-02-18_final
2023-02-19 10:50:48	ga_ls8c_ard_3-2-1_105078_2023-02-19_final
2023-02-20 09:52:22	ga_ls8c_ard_3-2-1_096071_2023-02-20_final
2023-02-20 09:54:45	ga_ls8c_ard_3-2-1_096077_2023-02-20_final
2023-02-21 10:36:48	ga_ls8c_ard_3-2-1_103074_2023-02-21_final
2023-02-22 09:43:09	ga_ls8c_ard_3-2-1_094079_2023-02-22_final
2023-02-22 11:21:38	ga_ls8c_ard_3-2-1_110078_2023-02-22_final
2023-02-22 11:24:01	ga_ls8c_ard_3-2-1_110084_2023-02-22_final
2023-02-23 10:27:35	ga_ls8c_ard_3-2-1_101082_2023-02-23_final
2023-02-24 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-02-23_final
2023-02-24 09:29:56	ga_ls8c_ard_3-2-1_092077_2023-02-23_final
2023-02-24 09:30:20	ga_ls8c_ard_3-2-1_092078_2023-02-24_final
2023-02-24 11:11:13	ga_ls8c_ard_3-2-1_108083_2023-02-24_final
2023-02-27 11:42:06	ga_ls8c_ard_3-2-1_113083_2023-02-27_final
2023-02-28 09:07:11	ga_ls8c_ard_3-2-1_088082_2023-02-27_final
2023-03-01 09:49:15	ga_ls8c_ard_3-2-1_095079_2023-03-01_final
2023-03-03 11:15:46	ga_ls8c_ard_3-2-1_109079_2023-03-03_final
2023-03-07 10:51:00	ga_ls8c_ard_3-2-1_105079_2023-03-07_final
2023-03-08 11:32:15	ga_ls8c_ard_3-2-1_112074_2023-03-08_final
2023-03-11 10:24:40	ga_ls8c_ard_3-2-1_101075_2023-03-11_final
2023-03-12 09:33:26	ga_ls8c_ard_3-2-1_092086_2023-03-12_final
2023-03-12 11:09:31	ga_ls8c_ard_3-2-1_108079_2023-03-12_final
2023-03-12 11:10:43	ga_ls8c_ard_3-2-1_108082_2023-03-12_final
2023-03-13 10:12:18	ga_ls8c_ard_3-2-1_099075_2023-03-13_final
2023-03-13 10:15:05	ga_ls8c_ard_3-2-1_099082_2023-03-13_final
2023-03-16 10:45:58	ga_ls8c_ard_3-2-1_104082_2023-03-16_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years